Declan Elliott

Facilitator interested in self-organizing systems and peer learning.

[Declan Elliott @declanelliott]

I gave up on Twitter years ago. Now that it’s new owners are embracing self verification, dialogue and the ability to both earn and spend on the platform I am returning. There are two primary forms of discourse. Discussion and dialogue. Twitter was the only platform which aspired to promote dialogue. It never got there under its previous ownership. Let’s see if it gets there under its current ownership.

[Cleo Abram @cleoabram]

The Demis Hassabis HUGE* Conversation (in full)

00:00 What is the hardest problem AI has already solved?
12:30 What is the cutting edge of drug discovery with AI?
21:53 Why did Demis say he “would have left AI in the lab longer”?
43:09 How should militaries use AI?
50:13 What can humans do that AI won't?
58:17 What does Demis Hassabis want his legacy to be?

(And 1:04:40 Can I beat Demis at Jenga?)

Recorded March 5, 2026 in London.

[Steven Sinofsky @stevesi]

"AI Eats the World" @benedictevans digs deep into the platform shift we are all living with AI. He asks questions, provides context, and offers a structure for how to think realistically about where we are heading without trying to be psychic. https://t.co/0stqXQaEIf

[Bill Gurley @bgurley]

A new @bgurley blog post!

I have been thinking about how sophisticated executives are using open source in super creative ways. Started writing this three years ago. Excited to finish it up and publish it! And with the new @p3institute brand.

https://t.co/W84vODq1ME

[Y Combinator @ycombinator]

Startup School is coming to Paris! 🇫🇷

Hear from founders like @lxbrun of @amilabs, @oliveur of @datadoghq, @kiwicopple of @supabase, @james406 of @posthog, and more.

And join the best builders and hackers from across France and Europe for a day of talks and sessions with YC partners.

[Y Combinator @ycombinator]

Demis Hassabis (@demishassabis) has had one of the most extraordinary careers in tech.

He started as a chess prodigy and video game designer at 17 before getting a PhD in neuroscience and going on to found DeepMind. His lab cracked Go, solved protein structure prediction with AlphaFold, and then gave it away free to every scientist on earth. That work won him the 2024 Nobel Prize in Chemistry. Today he leads @GoogleDeepMind, pushing toward the same goal he set as a teenager: AGI.

On this special live episode of How to Build the Future, he sat down with YC's @garrytan to talk about what still needs to happen to get us to AGI, his advice for founders on how to stay ahead of the curve, and what the next big scientific breakthroughs might be.

01:48 — What’s Missing Before We Get To AGI?
03:36 — Why Memory Is Still Unsolved
06:14 — How AlphaGo Shaped Gemini
08:06 — Why Smaller Models Are Getting So Powerful
10:46 — The 1000x Engineer
12:40 — Continual Learning and the Future of Agents
13:32 — Why AI Still Fails at Basic Reasoning
15:33 — Are Agents Overhyped or Just Getting Started?
18:31 — Can AI Become Truly Creative?
20:26 — Open Models, Gemma, and Local AI
22:26 — Why Gemini Was Built Multimodal
24:08 — What Happens When Inference Gets Cheap?
25:24 — From AlphaFold to the Virtual Cells
28:24 — AI as the Ultimate Tool for Science
30:43 — Advice for Founders
33:30 — The AlphaFold Breakthrough Pattern
35:20 — Can AI Make Real Scientific Discoveries?
37:59 — What to Build Before AGI Arrives

[Y Combinator @ycombinator]

AI has stopped being a feature and started being the foundation.

We're excited about a new wave of startups rebuilding software, services, and silicon— and pushing AI into the physical world.

https://t.co/QCIz6DnQnN

[Stephanie Zhan @stephzhan]

@karpathy and I are back! At @sequoia AI Ascent 2026. And a lot has changed. Last year, he coined “vibe coding”. This year, he’s never felt more behind as a programmer.

The big shift: vibe coding raised the floor. Agentic engineering raises the ceiling.

We talk about what it means to build seriously in the agent era. Not just moving faster. Building new things, with new tools, while preserving the parts that still require human taste, judgment, and understanding.

[Stripe @stripe]

We’re partnering with @Meta and @tempo so creators can receive stablecoins in their @link wallets.

[Apoorva Mehta @apoorva_mehta]

https://t.co/Mavrl0rGww

[Aaron Levie @levie]

Great read. AI lets you get tremendous leverage that wasn’t available before in almost any domain.

That means we’re at a unique moment in history where anyone with a high level of ambition and core skills in any area can overcome a lot of historical experience requirements for their role.

This can apply to anyone who’s junior or senior, but it’s pretty sweet that you can do far more than you could have accomplished as a newer employee than even a couple years ago. The people that take advantage of this will get ahead massively.

And the companies that find this talent within or outside should put them in key positions to get as much out of them as possible. These people will seem strange and from the future, but they will help you figure out where things are going. Everyone company should be doing whatever they can to find them.

[Dwarkesh Patel @dwarkesh_sp]

The Jensen Huang episode.

0:00:00 – Is Nvidia’s biggest moat its grip on scarce supply chains?
0:16:25 – Will TPUs break Nvidia’s hold on AI compute?
0:41:06 – Why doesn’t Nvidia become a hyperscaler?
0:57:36 – Should we be selling AI chips to China?
1:35:06 – Why doesn’t Nvidia make multiple different chip architectures?

Look up Dwarkesh Podcast on YouTube, Apple Podcasts, Spotify, etc. Enjoy!

[Patrick Collison @patrickc]

I'm lucky enough to have a great doctor and access to excellent Bay Area medical care. I've taken lots of standard screening tests over the years and have tried lots of "health tech" devices and tools.

With all this said, by far the most useful preventative medical advice that I've ever received has come from unleashing coding agents on my genome, having them investigate my specific mutations, and having them recommend specific follow-on tests and treatments.

Population averages are population averages, but we ourselves are not averages. For example, it turns out that I probably have a 30x(!) higher-than-average predisposition to melanoma. Fortunately, there are both specific supplements that help counteract the particular mutations I have, and of course I can significantly dial up my screening frequency. So, this is very useful to know.

I don't know exactly how much the analysis cost, but probably less than $100. Sequencing my genome cost a few hundred dollars.

(One often sees papers and articles claiming that models aren't very good at medical reasoning. These analyses are usually based on employing several-year-old models, which is a kind of ludicrous malpractice. It is true that you still have to carefully monitor the agents' reasoning, and they do on occasion jump to conclusions or skip steps, requiring some nudging and re-steering. But, overall, they are almost literally infinitely better for this kind of work than what one can otherwise obtain today.)

There are still lots of questions about how this will diffuse and get adopted, but it seems very clear that medical practice is about to improve enormously. Exciting times!

[Lex Fridman @lexfridman]

Here's my conversation with Jensen Huang, CEO of NVIDIA, the most valuable & one of the most influential companies in the history of human civilization. It is the engine powering the AI revolution.

This was a fascinating & inspiring conversation, in parts super-technical on engineering of every part of the AI stack, memory, power, supply chain (TSMC, ASML, etc), in parts about leadership & psychology, and in parts personal & philosophical about life, consciousness, mortality, and human nature.

It's here on X in full and is up everywhere else (see comment).

Timestamps:
0:00 - Introduction
0:33 - Extreme co-design and rack-scale engineering
3:18 - How Jensen runs NVIDIA
22:40 - AI scaling laws
37:40 - Biggest blockers to AI scaling laws
39:23 - Supply chain
41:18 - Memory
47:24 - Power
52:43 - Elon and Colossus
56:11 - Jensen's approach to engineering and leadership
1:01:37 - China
1:09:50 - TSMC and Taiwan
1:15:04 - NVIDIA's moat
1:20:41 - AI data centers in space
1:24:30 - Will NVIDIA be worth $10 trillion?
1:34:39 - Leadership under pressure
1:48:25 - Video games
1:55:16 - AGI timeline
1:57:29 - Future of programming
2:11:01 - Consciousness
2:17:22 - Mortality

[FT Technology News @fttechnews]

FT ranking: Europe’s leading start-up hubs 2026 https://t.co/qxBhrKQqNv

[Markus J. Buehler @ProfBuehlerMIT]

We are moving past the era of Big Data into the era of Big Discovery and we are shifting the role of machines from data processors to autonomous agents that understand their own limitations and proactively generate hypotheses to uncover universal principles of nature. We break down exactly how this happens - from category theory and first principles modeling to training AI models to embrace the unknown. Thank you @IngmarSchuster for having me on your "Machines and Molecules" podcast! Link to full podcast on YouTube and Spotify in reply.

[jack @jack]

we're making @blocks smaller today. here's my note to the company.

####

today we're making one of the hardest decisions in the history of our company: we're reducing our organization by nearly half, from over 10,000 people to just under 6,000. that means over 4,000 of you are being asked to leave or entering into consultation. i'll be straight about what's happening, why, and what it means for everyone.

first off, if you're one of the people affected, you'll receive your salary for 20 weeks + 1 week per year of tenure, equity vested through the end of may, 6 months of health care, your corporate devices, and $5,000 to put toward whatever you need to help you in this transition (if you’re outside the U.S. you’ll receive similar support but exact details are going to vary based on local requirements). i want you to know that before anything else. everyone will be notified today, whether you're being asked to leave, entering consultation, or asked to stay.

we're not making this decision because we're in trouble. our business is strong. gross profit continues to grow, we continue to serve more and more customers, and profitability is improving. but something has changed. we're already seeing that the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. and that's accelerating rapidly.

i had two options: cut gradually over months or years as this shift plays out, or be honest about where we are and act on it now. i chose the latter. repeated rounds of cuts are destructive to morale, to focus, and to the trust that customers and shareholders place in our ability to lead. i'd rather take a hard, clear action now and build from a position we believe in than manage a slow reduction of people toward the same outcome. a smaller company also gives us the space to grow our business the right way, on our own terms, instead of constantly reacting to market pressures.

a decision at this scale carries risk. but so does standing still. we've done a full review to determine the roles and people we require to reliably grow the business from here, and we've pressure-tested those decisions from multiple angles. i accept that we may have gotten some of them wrong, and we've built in flexibility to account for that, and do the right thing for our customers.

we're not going to just disappear people from slack and email and pretend they were never here. communication channels will stay open through thursday evening (pacific) so everyone can say goodbye properly, and share whatever you wish. i'll also be hosting a live video session to thank everyone at 3:35pm pacific. i know doing it this way might feel awkward. i'd rather it feel awkward and human than efficient and cold.

to those of you leaving…i’m grateful for you, and i’m sorry to put you through this. you built what this company is today. that's a fact that i'll honor forever. this decision is not a reflection of what you contributed. you will be a great contributor to any organization going forward.

to those staying…i made this decision, and i'll own it. what i'm asking of you is to build with me. we're going to build this company with intelligence at the core of everything we do. how we work, how we create, how we serve our customers. our customers will feel this shift too, and we're going to help them navigate it: towards a future where they can build their own features directly, composed of our capabilities and served through our interfaces. that's what i'm focused on now. expect a note from me tomorrow.

jack

[John Collison @collision]

Eric Glyman @eglyman runs @tryramp, which now powers >2% of US corporate spend. @arampell and I dug in with him on why financial systems have proven resistant to automation, the second-order effects of AI on business, and Ramp’s strategy.

[Chris Fralic @chrisfralic]

Congrats all around. This interview was a clever part of the interview process - reminded me I once pitched the entire Benchmark team when we were raising money at Del icio us - they were taller then but remain legendary.

[Garry Tan @garrytan]

Boil the Oceans

You know the phrase: “don’t boil the ocean.” Everyone’s said it in some overly ambitious meeting. It’s good advice in normal times. It keeps teams focused. It prevents scope creep. But we are no longer in normal times, and I think it’s time to retire saying it.

Artificial Superintelligence means it’s time to boil the ocean. We’ll start with a few lakes first.

I was recently with a university endowment’s head of private investing who told me their engineers were terrified for their jobs after seeing what Claude Code could do. And I get it — that’s the natural first reaction. But it’s the wrong one. It’s a zero-sum reaction to a positive-sum moment.

Instead of worrying about doing the same thing we’ve been doing for cheaper, why not focus on doing the thing we never even dreamed of doing? Why can’t that endowment achieve 50% net IRR instead of 10%? Why can’t a startup deliver a service that is 100x better than the incumbent? Why can’t we have fusion energy? Why can’t we talk to every single user and have a perfect understanding of every bug in our product?

These aren’t rhetorical questions anymore. They’re engineering problems with paths to solutions.

Here is what I think is actually going on with the fear: our fear of the future is directly proportional to how small our ambitions are. If your plan is to keep doing exactly what you’re doing, then yes, a machine that can do it faster and cheaper is terrifying. But if your plan is to do something dramatically bigger, then the machine is the best news you’ve ever gotten.

If you’re a worker — someone who trades labor for a living — this is the moment to become a builder. Start a business. And if you’re already management or capital, it’s time to go 10x more hardcore on what your aspirations could be. Not eking out 5% efficiency gains. Not increasing profit margins 2% by lowering cost and firing people. Those are the old games. The new question is: what would it look like to build a product or service so good that people would happily pay 10x what they pay now?

The net result of this is more jobs, not fewer. As Ryan Petersen likes to say, the human desire for more things is absolutely limitless. We can actually fulfill that desire now — if we have the agency to prompt it for ourselves.

Buckminster Fuller coined the term “ephemeralization” in 1938: doing more and more with less and less until eventually you can do everything with nothing. His entire vision of progress was about technology enabling radical expansion of human capability through dematerialization. He traced this from stone bridges to iron trusses to steel cables — each iteration stronger, longer, lighter, cheaper. He wasn’t describing job destruction. He was describing civilization getting better at being civilization.

This is Jevons Paradox for everything. When you make a resource dramatically more efficient, you don’t use less of it — you use vastly more. Steam engines didn’t reduce coal consumption. They made coal so useful that demand exploded. The same thing is about to happen with intelligence, with labor, with every service and product we can imagine.

But Jevons Paradox doesn’t activate on its own. It requires capital and management to actually raise their ambitions — to boil lakes and oceans instead of drowning them in committee

That’s what startups have always been good at: moving fast in the face of radical uncertainty, building for the 10x future while everyone else is optimizing for the 1.05x present.

Time to start.

[Chris Dixon @cdixon]

https://t.co/zAHyO5TJ0c